mlsanityData to 7 Oct 2026

Sketch2Manga: Shaded Manga Screening from Sketch with Diffusion Models

arXiv 2403.08266 ↗First posted 13 Mar 2024cs.CV cs.GRcited by 2

On the map: Diffusion models → Image generation, text-to-image and editing

Abstract (arXiv)

While manga is a popular entertainment form, creating manga is tedious, especially adding screentones to the created sketch, namely manga screening. Unfortunately, there is no existing method that tailors for automatic manga screening, probably due to the difficulty of generating high-quality shaded high-frequency screentones. The classic manga screening approaches generally require user input to provide screentone exemplars or a reference manga image. The recent deep learning models enables the automatic generation by learning from a large-scale dataset. However, the state-of-the-art models still fail to generate high-quality shaded screentones due to the lack of a tailored model and high-quality manga training data. In this paper, we propose a novel sketch-to-manga framework that first generates a color illustration from the sketch and then generates a screentoned manga based on the intensity guidance. Our method significantly outperforms existing methods in generating high-quality manga with shaded high-frequency screentones.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Image generation, text-to-image and editing, one of 14 directions in Diffusion models. Builds on 7 of its 20 references that are in the map. First posted on arXiv 13 Mar 2024.

Builds on

7 of 20 references.

Closest ancestors · 2

Same direction, newest first

  1. 2023Designing a Better Asymmetric VQGAN for StableDiffusion7 Jun
  2. 2023Adding Conditional Control to Text-to-Image Diffusion Models10 Feb

Other references · 5

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  3. 2022Generative Adversarial Networkscited by 5,603
  4. 2016Image-to-Image Translation with Conditional Adversarial Networkscited by 4,510
  5. 2021Exploiting Aliasing for Manga Restorationcited by 10

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 0; 2026: 1.

2 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2023AnimeDiffusion: Anime Face Line Drawing Colorization via Diffusion Models
  2. 2025Interactive Drawing Guidance for Anime Illustrations with Diffusion Model
  3. 2024MangaUB: A Manga Understanding Benchmark for Large Multimodal Models
  4. 2024KnobGen: Controlling the Sophistication of Artwork in Sketch-Based Diffusion Models
  5. 2025AnimeColor: Reference-based Animation Colorization with Diffusion Transformers
  6. 2023DiffSketching: Sketch Control Image Synthesis with Diffusion Models
  7. 2024Alfie: Democratising RGBA Image Generation With No
  8. 2024Sketch2NeRF: Multi-view Sketch-guided Text-to-3D Generation